COACHES: An assistance multi-robot system in public areas

Abstract

Abstract-In this paper, we present a robust system of selfdirected autonomous robots evolving in a complex and public spaces and interacting with people. This system integrates highlevel skills of environment modeling using knowledge-based modeling and reasoning and scene understanding with robust image and video analysis, distributed autonomous decisionmaking using Markov decision process and Petri-Net planning, short-term interacting with humans and robust and safe navigation in overcrowding spaces. This system has been deployed in a variety of public environments such as a shopping mall, a center of congress and in a lab to assist people and visitors. The results are very satisfying showing the effectiveness of the system and going beyond just a simple proof of concepts.

Robotics Utilization in Automatic Vision-Based Assessment Systems From Artificial Intelligence Perspective: A Systematic Review

“…The developed framework is a 3D human recognition and tracking framework that possesses advanced capabilities in environment modelling and scene comprehension. It enabled the robots to make autonomous decisions, engage with humans in a short period and navigate safely in crowded public areas [90]. A robotic testbed incorporating a face detection and recognition hardware tracking system was proposed [8].…”

“…[65], [1], [72], [14], [90] Knowledge base Primary The knowledge base of input variables is stored as data structure and defined by the researchers to model considerable static/dynamic knowledge about the environment and to propose an intelligent system. [67] Knowledge chunk KC Primary The database stores the KCs, which are components of the reusable workflow, the indexes base necessary for searching and the video recording of robots moving in accordance with the workflow components.…”

“…Another emerging challenge for the near future is designing cooperative robots skilled for aiding in public places; these robots can share tasks and communicate with humans [90]. The fundamental issues that must be addressed include the robust system design of self-directed autonomous robots with advanced environment modelling and scene understanding capabilities, distributed autonomous decision-making, short-term interaction with humans and robust and safe navigation in crowded spaces [90].…”